The present invention relates to compression of ultrasound signal data received by ultrasound transducers, particularly to compressing ultrasound signal samples after analog to digital conversion and prior to beamforming, detection and image formation.
Medical ultrasound systems scan the internal anatomy of a subject by transmitting ultrasound beams from a transducer placed on the subject by a clinician. The ultrasound waves are reflected at interfaces of internal tissues having different acoustic impedances, producing echoes. The transducer receives the echoes and converts them to electrical ultrasound signals. The ultrasound system applies a sequence of processing steps to the ultrasound signals to produce an image or series of images that are displayed at a control console for analysis by the clinician. Images formed based on the strength of the received echo are referred to as B-mode images. In addition, the system can measure the Doppler shifts of the ultrasound signals to produce color images indicating the flow of fluid, such as blood, and perform additional analyses useful for diagnosis.
A conventional medical ultrasound transducer includes an array of piezoelectric elements that transmit ultrasound waves when driven by electrical signals, receive the returning echoes and convert the received echoes to a plurality of analog signals. A plurality of analog to digital converters (ADCs) sample the analog signals, each producing a stream of digital signal samples. Typical digital signal processing of the signal samples includes beamforming, downconversion, B-mode (brightness) processing and/or Doppler processing, scan-conversion and image processing for display. The beamformer delays and combines the streams of signal samples to form an array of beamformed samples corresponding to a particular direction in the field of view. The beamformer can produce a number of arrays of beamformed samples corresponding to a number of directions in the field of view. Depending on the type of diagnostic information desired, B-mode processing and/or Doppler processing are then performed on the beamformed samples to form B-mode detected samples and/or Doppler detected samples. The spatial coordinates of the detected samples still correspond to the beam geometry of the beamformed samples. The scan converter performs coordinate transformations of the detected samples to produce frames of data having a raster format appropriate for display. Additional image processing is applied to the frames of samples to allow their display as two-dimensional (2-D) or three-dimensional (3-D) images.
Current efforts for improving medical ultrasound systems are directed to increasing the diagnostic capabilities of console/cart systems and developing smaller portable devices with improved image quality. For the high-end console or cart systems, it is desirable to increase the number of transducer elements to produce higher resolution and/or 3-D images to expand the diagnostic capability. Increasing the number of transducer elements increases the amount of data communicated from the transducer head to the console processor, which can require a higher bandwidth communication channel and a larger cable connection. The data acquisition capacity of the transducer head is constrained by requirements for manipulation and form factors. Hand-carried and handheld ultrasound devices are economical and desirable for use in small clinics, mobile treatment units and the home. For these devices, battery life is also a constraint. More efficient processing, transfer and storage of ultrasound signal data in the ultrasound system can conserve power, data transfer bandwidth and memory capacity.
Compression of ultrasound signal data can provide benefits for both console/cart systems and portable systems. The benefits include reducing the data transfer bandwidth, memory capacity and power requirements of the system. For a portable or hand-carried ultrasound system, these benefits reduce weight and increase battery life. For a console system, compression mitigates the impact of increasing amounts of data acquired by the transducer head and transport of the data to the ultrasound signal processor. Compression that is computationally efficient introduces the benefits of compression with low or no impact on system complexity.
The present description uses the term “compression” to refer to data compression of ultrasound signal samples where the number of bits representing the signal samples is reduced and the signal samples are later decompressed prior to processing for display. Some descriptions of ultrasound imaging systems use the term compression to mean “pulse compression,” not data compression. Pulse compression refers to filtering and/or modulation of the transmitted ultrasound pulses and inverse filtering and/or demodulation of the received ultrasound pulses. (For example, see “Parameter optimization of pulse compression in ultrasound imaging system with coded excitation,” by V. Behar and D. Adam in Ultrasonics vol. 42, pp. 1101-1109, 2004.) Some descriptions of ultrasound imaging systems use the term compression to mean “log compression,” not data compression. In that context, log compression refers to calculating the logarithm of processed ultrasound data, typically the magnitude detected data prior to display. (For example, see “Signal Processing Overview of Ultrasound Systems for Medical Imaging,” by A. Murtaza et al., Texas Instruments SPRAB 12, pp. 1-26, November 2008). Both pulse compression and log compression intentionally change characteristics of the transmitted or received ultrasound signals in the time domain and frequency domain. Data compression of the received ultrasound signal samples followed later by decompression is a process that preserves the signal characteristics in the time and frequency domains. The present description refers to lossless and lossy compression of ultrasound signal samples. In lossless compression, the decompressed samples have identical values to the original samples. In lossy compression, the decompressed samples are similar, but not identical, to the original samples. The present description uses to the term “frame” to refer to an array of ultrasound data, either raw or processed, that is eventually processed to form an ultrasound image for display. Descriptions of ultrasound imaging systems in the art also use the term “screen” to refer to a frame of ultrasound data. In the present description, “real time” means a rate that is at least as fast as the sample rate of a digital signal. The term “real time” can be used to describe rates for processing, transfer and storage of the digital signal. The sample rate is the rate at which an ADC forms samples of a digital signal during conversion of an analog signal. Some descriptions of ultrasound imaging systems in the art use the term “real time” to refer to the frame rate for display of the ultrasound images. The present description relates real time to the sample rate instead of the frame rate interpretation.
Previous applications of data compression in ultrasound systems have included alternatives for data compression before and after scan conversion for image formation. In U.S. Pat. No. 6,315,722 entitled “Ultrasonic Diagnostic Device,” issued on Nov. 13, 2001, Yaegashi describes a time axis extension unit for storing ultrasound signal samples output from an ADC unit. The time axis extension unit writes the data at the rate output from the ADC unit and reads the data out at a lower rate. The time axis extension unit stores signal samples for one screen, or frame, and can be implemented using first-in first-out (FIFO) memories. A data compression unit compresses signal samples read from the time axis extension unit. Yaegashi describes applying image compression technologies, such as methods based on the discrete cosine transform (DCT) for exploiting spatial correlation within one frame of data or MPEG compression methods for multiple frames of data. (MPEG refers to the video data compression standards developed by the Moving Picture Experts Group.) The compressed samples are stored in a mass memory device, such as a hard disk. The data compression reduces the storage capacity needed in the mass memory device. For producing an image, a data expanding unit decompresses the compressed samples retrieved from the mass memory device. Conventional operations, including filtering, logarithmic conversion, detection and digital scan conversion, are applied to the decompressed samples for image formation and display. Yaegashi does not disclose beamforming in the processing sequence.
In the US Patent Publication, publication number 2008/0114246, entitled “Transducer Array Imaging System,” Randall et al. describe compressing ultrasound digital data using mapping, resampling and/or data windowing before and/or after beamforming. The mapping can include requantizing or clipping signal samples. For example, the number of required bits decreases monotonically with depth so that fewer bits per sample may be assigned based on depth. In some embodiments, signal samples from receive channels extending beyond the transmit and receive apertures may be truncated. For imaging a region of interest (ROI), signal acquisition time may be proportional to depth range, so that data acquired before a minimum sample time and/or after a maximum sample time may be truncated if they do not contribute to the formation of image pixels. In some embodiments, the data may be resampled to fewer samples if the display resolution is less than required for full resolution imaging, thus reducing the number of samples transferred.
In U.S. Pat. No. 6,042,545 entitled “Medical Diagnostic Ultrasound System and Method for Transform Ultrasound Processing,” issued Mar. 28, 2000, Hossack et al. describe transform compression techniques for ultrasound data after beamforming. Alternatives for beamforming include analog beamforming prior to the ADC or digital beamforming after the ADC. The beamformer generates in-phase and quadrature (I and Q) samples or, alternatively, radio frequency (RF) samples. Beamformed samples corresponding to a two-dimensional (2-D) frame are filtered and transformed to produce a transform domain representation. The transform domain samples are quantized and/or encoded for compression. The compression may be lossless or lossy. Any transform, such as the DCT or the Discrete Wavelet Transform (DWT), quantization function and encoding function may be applied for compressing the frame of data. For example, JPEG compression includes dividing the frames of data into 2-D blocks of data, transforming using a 2-D DCT on each of the blocks, quantizing the transform domain samples, differentially encoding the DC (zero frequency) transform samples between blocks, and entropy encoding the 2-D blocks of quantized transform domain samples (e.g. Huffman encoding). The JPEG compression algorithms can be configured as lossy or lossless. (JPEG compression refers to the standard image compression methods developed by the Joint Photographic Experts Group.) Additional operations in the transform domain for various image processing functions, such as filtering, are more computationally efficient in the transform domain than the spatial domain. For example, 2-D filtering in the spatial domain uses 2-D convolution operations. In the transform domain 2-D filtering uses more efficient multiplications by the transform domain filter coefficients. The compressed transform domain data can be stored for later image formation. For decompression, the inverse encoding and transform functions are applied prior to processing for display.
In the U.S. Pat. No. 6,855,113, entitled “Diagnostic Information Generation Apparatus and Ultrasonic Diagnostic System,” issued Feb. 15, 2005, Amemiya et al. describe compressing frames of ultrasound data prior to wireless transmission from an ultrasonic wave unit to an information unit. The ultrasonic wave unit includes the transducer and a processor for subsequent beamforming, B-mode imaging and Doppler imaging. General purpose data compression standards are applied to the B-mode imaging data or Doppler imaging data, such as JPEG compression for a single frame or MPEG compression for multiple frames. The compressed data are transmitted using a standard wireless communication modality to the information unit. The information unit includes a central processing unit (CPU) that decompresses the received data in accordance with the compression standard. The CPU further processes the decompressed B-mode imaging data and decompressed Doppler imaging data for display.
In the PCT published application, international publication number WO 97/09930, entitled “Ultrasonic Diagnostic Apparatus for Compressing and Storing Data in CINE Memory,” published Mar. 20, 1997, Lee describes compressing ultrasound data prior to storage in a CINE memory and decompressing data retrieved from the CINE memory. A CINE memory includes several banks organized by time. In this system, the ultrasonic probe performs beamforming prior to the ADC, so the ADC output data represent beamformed samples. Compression is applied to a frame of data and can be applied before or after scan conversion. The Lempel-Ziv-Welch (LZW) algorithm is applied for compression and decompression. The LZW algorithm is based on detecting repeated patterns of bits in the data and assigning codes to the repeated patterns. The compressed data for a frame retrieved from the CINE memory are decompressed and further processed for display.
In the Japanese patent application, publication number 2005-081082, entitled “Ultrasonograph and Ultrasonic Data Compression Method,” published Mar. 31, 2005, Akihiro describes three embodiments for compressing ultrasound data after analog beamforming. In the first embodiment, an ADC generates I and Q samples of the analog beamformer output signals. The compressor calculates the differences between the I,Q samples of adjacent beams followed by run-length encoding of the differences to form the compressed data. The compressed data are stored in memory. Compressed data retrieved from memory are decompressed and processed for image display. In the second embodiment, an ADC generates RF samples of the analog beamformer output samples. The compressor calculates differences between the RF samples of adjacent beams followed by run-length encoding. The compressed samples are stored in memory, retrieved, decompressed and processed for image display. In the third embodiment, beamformer output is further processed to generate B-mode image frames and Doppler image frames prior to compression. The compressor calculates frame to frame differences to produce compressed data frames. The compressed data frames are stored in memory, retrieved, decompressed and further processed for display.
In the U.S. Pat. No. 4,751,929, entitled “Ultrasonic Bloodstream Diagnostic Apparatus with Dual Displays of Velocity Profiles and Average Flow Velocity,” issued Jun. 21, 1988, Hayakawa et al. describe compressing Doppler frequency detected data. The compressor operates on the output of a squaring and adding circuit that calculates the magnitude squared of the real and imaginary parts of the frequency spectrum samples. The compressor re-encodes the bits of each sample output from the adder to reduce the number of bits in the representation. The compressor operates on the adder output sample to encode the location of the most significant bit in the mantissa, preserve a fixed number of most significant bits and remove the remaining least significant bits. The resulting compressed word for each sample includes the fixed number of most significant bits and a code indicating the number of least significant bits eliminated from the original sample. A variable number of least significant bits are removed from each sample, so the compression is lossy.
In the paper entitled “A Novel B-Mode Ultrasound Image Compression Method Based on Beam Forming Data,” 1998 Proc. Intl. Conf. IEEE Engineering in Medicine and Biology Society, Vol. 20 No. 3, pp. 1274-76, Li et al. describe compressing beamformed samples for transmission in a tele-ultrasound system. The DWT is applied to a frame of 128×512 beamformed samples. The coefficients of subimages in the vertical direction are quantized and encoded using arithmetic coding. After decompression, scan conversion is applied to the frame of 128×512 decompressed samples to form the frame of 512×512 samples for display.
Several papers describe different methods for compressing ultrasound images after scan conversion for image formation. A few examples include the following. In the paper entitled “Comparative Survey of Ultrasound Images compression Methods Dedicated to a Tele-Echography Robotic System,” 2001 Proc. 23rd Annual IEEE Engineering in Medicine and Biology Society Intl. Conf., pp. 2461-64, Delgorge et al. describe applying different compression methods to ultrasound images. The methods include Fourier transform, DCT, quadtree decomposition, DWT, fractals, histogram thresholding and run length coding. The methods are applied to 512×512 ultrasound images after scan conversion. In the paper entitled “Despeckling of Medical Ultrasound Images Using Data and Rate Adaptive Lossy Compression,” IEEE Trans. Medical Imaging, vol. 24, No. 6, June 2005, pp. 743-54, Gupta et al. describe combining compression with an algorithm to remove speckle from the ultrasound image. The DWT is followed by the speckle removal algorithm, quantization and entropy encoding. In the paper entitled “A Tele-Operated Mobile Ultrasound Scanner Using a Light-Weight Robot,” IEEE Trans. Information Technology in Biomedicine, Vol. 9, No. 1, March 2005, pp. 50-58, Delgorge et al. describe applying various lossless and lossy compression methods to ultrasound images. The lossless methods include Huffman, arithmetic coding, Lempel-Ziv, run length coding and Fano coding. The lossy methods include various JPEG versions, including JPEG, JPEG-LS and JPEG2000. In the paper entitled “Maximum Likelihood Motion Estimation in Ultrasound Image Sequences,” IEEE Signal Processing Letters, Vol. 4, No. 6, June 1997, pp. 156-7, Strintzis et al. describe applying MPEG compression to a sequence of ultrasound images. The method includes detecting motion vectors for 8×8 blocks of pixels between consecutive frames in the sequence of images. The motion vectors are encoded for frame to frame MPEG compression.
The commonly owned U.S. Pat. No. 7,009,533 (the '533 patent), entitled “Adaptive Compression and Decompression of Bandlimited Signals”, dated Mar. 7, 2006, describes algorithms for compression and decompression of certain bandlimited signals. The commonly owned U.S. Pat. No. 7,088,276 (the '276 patent), entitled “Enhanced Data Converters Using Compression and Decompression,” dated Aug. 8, 2007, describes applying lossless or lossy compression to signal samples output from an ADC implemented in a single integrated circuit. The commonly owned and copending U.S. patent application Ser. No. 12/120,988 (the '988 application), filed May 15, 2008, entitled “Digital Interface for Data Converters,” describes multiplexing data output from multiple ADCs in parallel to reduce the number of active data ports at the digital interface.
There is a need for efficient data transfer and storage of ultrasound signal data between components of the ultrasound imaging system. There is a need for computationally efficient data compression of ultrasound signal data to improve data transfer and storage capacity with minimal impact on system complexity.